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Model Validation Techniques

Learn validation strategies to test model generalization and avoid overfitting.

📄️ Train-Test Split

Mastering the data partitioning process to ensure unbiased model evaluation.

📄️ K-Fold Cross-Validation

Mastering robust model evaluation by rotating training and testing sets to maximize data utility.

📄️ LOOCV

The most exhaustive validation technique: training on N-1 samples and testing on a single observation.